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Rethinking value construction in biomedicine and healthcare

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Abstract

Despite longstanding attempts to conceptualise and measure value in biomedicine and healthcare, there is no single agreed definition of what value is. Instead, and as such, value is often taken as given or constructed in economic terms. In this paper, we argue that taking the meaning of value as given, or reverting to technocratic or economic dimensions of value, obscures the non-technical and societal dimensions of value construction and operationalisation in healthcare and biomedical practices. Through a comparative study of five cases of biomedicine and healthcare, we aim to bring out the socioeconomic and political processes that make a thing valuable for society and its implications. Our contention is that a clearer understanding of what makes something valuable (or not) is the first step towards what socially reflexive and responsible valuing of biomedicine and healthcare ought to be.

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Notes

  1. See other definitions of value in Dussauge et al. (2015) and Birch (2017).

  2. https://publications.parliament.uk/pa/cm201719/cmselect/cmsctech/349/34908.htm#footnote-067.

  3. https://www.england.nhs.uk/2014/08/nhs-world-leader/.

  4. https://www.genomicsengland.co.uk/about-genomics-england/the-100000-genomes-project/.

  5. https://www.thelancet.com/journals/lancet/article/PIIS0140-6736(14)62453-3/fulltext?showall=true%3D.

  6. https://www.genomicsengland.co.uk/about-genomics-england/the-100000-genomes-project/.

  7. Woods provides an example of such rhetoric, which appeared on GEL’s website: “Genomics England, with the consent of participants and the support of the public, is creating a lasting legacy for patients, the NHS and the UK economy, through the sequencing of 100,000 genomes” (Woods 2016, pp. 177, 229).

  8. Such as model transparency (how an algorithm is constructed), data bias (which data are used or not and how algorithms might change if used), data anonymisation (privacy concerns), calibration (fitting statistical prediction to the risk threshold where patient requires treatment) reduce clear clinical risk perceptions (see e.g. Datta Burton et al. 2021; Shah et al. 2018; Wessler et al. 2017).

  9. https://www.nature.com/articles/d41586-019-03574-5.

  10. https://www.nbcnews.com/business/consumer/trust-facebook-has-dropped-51-percent-cambridge-analytica-scandal-n867011.

  11. The full set of principles is that (1) focus should not only be on lowering costs but also on value for patients; that (2) competitions must be based on results; that (3) competition should revolve around medical conditions and over the full cycle of care; that (4) high-quality care should be less costly; that (5) value must be driven by provider experience, scale and learning at the medical condition level; (6) competition should be regional and national, not just local; (7) results information to support value-based competition must be widely available; and (8) innovations that increase value must be strongly rewarded (Porter and Teisberg 2006).

  12. https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/Value-Based-Programs/HVBP/Hospital-Value-Based-Purchasing.html.

  13. An example for voluntary measures is the establishment of Accountable Care Organizations (ACO).

  14. At the time of its inception, CMS intended for VBP to be budget-neutral for Medicare; “any additional costs associated with quality improvement must be offset by other reduction in cost” (Tompkins et al, 2009, w252).

  15. The latter are calculated in, very broadly speaking, the following way: using selected measures from CMS’ Hospital Inpatient Quality Reporting Program, the quality of a hospital’s performance on mortality and complications, healthcare-associated infections, patient safety, patient experience, process, and efficiency and cost reduction are assessed.

  16. According to the authors, lower margins of public v. private hospitals mean fewer resources being available to be channelled into quality improvement and maintenance (including teaching, training, tracking and analysing performance, etc.; Dupree et al. 2014).

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Acknowledgements

We would like to convey our special thanks to Professor Bobbie Farsides, Genomics England, Dr Angela Filipe and Dr Clemence Pinel for comments on previous versions of this manuscript, and to all who participated in this research. This work was supported by the Austrian Science Fund (FWF Grant Number V561), the UK Engineering and Physical Sciences Research Council (PETRAS 2 Grant Number EP/S035362/1), the European Commission Horizon 2020 (Human Brain Project Special Grant Agreement 2 number 785907) and the Wellcome Trust (Grant Number 086034).

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  1. Department of Science, Technology, Engineering and Public Policy (UCL STEaPP), University College London, London, UK

    Saheli Datta Burton & Gabrielle Samuel

  2. Centre for the Study of Contemporary Solidarity, Department of Political Science, University of Vienna, Vienna, Austria

    Saheli Datta Burton, Katharina Kieslich, Katharina Theresa Paul & Barbara Prainsack

  3. Department of Global Health and Social Medicine, King’s College London, Bush House, London, UK

    Saheli Datta Burton, Gabrielle Samuel & Barbara Prainsack

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Datta Burton, S., Kieslich, K., Paul, K.T. et al. Rethinking value construction in biomedicine and healthcare. BioSocieties 17, 391–414 (2022). https://doi.org/10.1057/s41292-020-00220-6

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  • DOI: https://doi.org/10.1057/s41292-020-00220-6

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